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Found 6,606 Skills
Synthesize GitHub delivery context into a concise Basic Memory project update. Use in CI after `bm ci collect` prepares a ProjectUpdateContext; return only structured AgentSynthesis JSON for `bm ci publish`.
Conventions for writing sharp, concise prose and Markdown, for human readers and AI agents. Read before writing or editing documentation, READMEs, instructions, agent skills, or any prose text.
AE Agent system administration CLI for root and agent administrators. Use when the user asks to manage Agent members, sandboxes and shared tools, company model visibility/defaults/pricing, usage statistics and exports, cost quotas, balance alerts, or IM channels. Must use ae-cli system commands, discover real IDs before writes, and never attempt to bypass a permission denial.
Build AI agents with structured access to Sanity content via Sanity Context. Use when setting up a Sanity-powered chatbot, connecting an AI assistant to Sanity content, or adding client-side tools to an agent. Covers Studio setup, agent implementation, and advanced patterns. Always use this skill when users mention building a chatbot with Sanity, creating an AI assistant for their content, setting up the Sanity Context MCP server, integrating Sanity with Claude/GPT/any LLM, making content searchable by AI, implementing semantic search over Sanity data, or connecting their CMS to an AI agent.
Install the Datadog Agent on Kubernetes using the Datadog Operator — required before enabling Single Step Instrumentation (SSI), which automatically instruments applications for APM without code changes. Only use if no Datadog Agent is deployed on the cluster yet.
Use when a developer wants to iterate on ONE specific Agent Observability / LLM Obs trace whose output they didn't like — re-running that trace against their LOCAL code, seeing a concise diff of the old vs new output, and looping (change code → replay → diff) until satisfied. Invoked as /agent-observability-replay-trace <trace-id> [changes to test]. Signals: "replay this trace"; "iterate on a trace"; "this trace's output is wrong, fix it and re-run"; "re-run trace <id> with <change>"; pasting a trace id from the Agent Observability UI with a description of what to fix. It fetches the trace via the datadog-llmo MCP or the pup CLI, edits code, re-runs the app to emit a NEW trace, and diffs the two — no local server, no browser. For agents traced with ddtrace / LLM Obs (Python first-class), with JSON-serializable entry input. Do NOT use for: scored Experiments or the browser "Replay" button (that's agent-observability-replay-experiment), building an experiment from a dataset/CSV, writing evaluators, root-causing failed traces, or RUM/HTTP session replay.
(NS) Full post-harness-init bootstrap in one session — architecture rules, sync, brownfield map, reverse business spec, project AGENTS.md. Use for "harness prepare", post-install setup, onboard brownfield, or running all prepare skills without separate slash commands. Do NOT use for greenfield with no app code, single-skill runs, or CLI-only baseline AGENTS.md.
Persist gotchas, preferences, or a repeated workflow from recorded agent history into AGENTS.md or a new skill. Use when the user asks to extract lessons from past sessions or turn prior agent work into a skill.
Read this BEFORE launching any subagent (Task tool, background agents, parallel agents, best-of-N, delegating work to another agent). Hard model rules for subagents plus consensus principles for using them well. Triggers: launch a subagent, spawn agents, run agents in parallel, delegate to a subagent.
Search, score, scan, and import agent skills from GitHub repositories that contain SKILL.md, CLAUDE.md, .cursorrules, and similar agent skill files. Discover community skills across many tool and provider categories, evaluate relevance with heuristic scoring, check for malware or hardcoded secrets, and install into Hermes, Claude Code, Gemini CLI, or OpenCode agent directories.
Design ObjectStack AI skills, tools, knowledge sources, conversations, model registry entries, and MCP integrations. Use when the user is adding `*.skill.ts` / `*.tool.ts`, configuring an LLM provider, wiring agent tools, or indexing ObjectStack data as a knowledge source for RAG. Agents themselves are platform-internal (`ask` / `build`) — third parties extend them via skills and tools, not by authoring `*.agent.ts`. Do not use for general LLM prompting questions unrelated to ObjectStack metadata.
Use when a developer asks their coding agent to initialize or work with moldea; plan an AI- or agent-enabled system and decide what should be agents versus deterministic software, services, tools, or human control; create or refine an AI agent or its behavioral system, including instructions, descriptions, handoff descriptions, tools, skills, schemas, variables and providers, routing or handoffs, bindings, or runtime integration; evaluate, reconcile, or validate an existing moldea system; or make ordinary behavior-affecting repository changes that may require maintaining an adopted moldea system. Loading the skill does not adopt moldea: initial adoption still requires explicit developer intent, while relevance-triggered maintenance applies once a repository uses or is adopting moldea.